README.md

Analysis-of-Stock-High-Frequent-Data-with-ML

Introduction

This project aims at predicting stock price based on high frequency stock data. There is a big difference between
high frequency data and others, thus certain preprocessing methods are necessary in mining useful information.
LSTM is again proved effective in this problem. As a contrast, we also tested some other classical machine learning model such as
XGBoost and random forest.

Experiment

Prediction of next tick's price:

We use LSTM to predict stock price, mid-price of next tick. Random Forest and XGBoost are used to classify the following price trend.